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Recent advances in large reconstruction and generative models have significantly improved scene reconstruction and novel view generation. However, due to compute limitations, each inference with these large models is confined to a small…

Computer Vision and Pattern Recognition · Computer Science 2025-04-15 Shangjin Zhai , Zhichao Ye , Jialin Liu , Weijian Xie , Jiaqi Hu , Zhen Peng , Hua Xue , Danpeng Chen , Xiaomeng Wang , Lei Yang , Nan Wang , Haomin Liu , Guofeng Zhang

We present a method for generating Streetscapes-long sequences of views through an on-the-fly synthesized city-scale scene. Our generation is conditioned by language input (e.g., city name, weather), as well as an underlying map/layout…

Computer Vision and Pattern Recognition · Computer Science 2024-07-26 Boyang Deng , Richard Tucker , Zhengqi Li , Leonidas Guibas , Noah Snavely , Gordon Wetzstein

This paper presents a new method to synthesize an image from arbitrary views and times given a collection of images of a dynamic scene. A key challenge for the novel view synthesis arises from dynamic scene reconstruction where epipolar…

Computer Vision and Pattern Recognition · Computer Science 2020-04-06 Jae Shin Yoon , Kihwan Kim , Orazio Gallo , Hyun Soo Park , Jan Kautz

Urban scene synthesis with video generation models has recently shown great potential for autonomous driving. Existing video generation approaches to autonomous driving primarily focus on RGB video generation and lack the ability to support…

Computer Vision and Pattern Recognition · Computer Science 2026-03-16 Guile Wu , David Huang , Dongfeng Bai , Bingbing Liu

Generating novel views of an object from a single image is a challenging task. It requires an understanding of the underlying 3D structure of the object from an image and rendering high-quality, spatially consistent new views. While recent…

Computer Vision and Pattern Recognition · Computer Science 2023-12-05 Jeong-gi Kwak , Erqun Dong , Yuhe Jin , Hanseok Ko , Shweta Mahajan , Kwang Moo Yi

We introduce a film score generation framework to harmonize visual pixels and music melodies utilizing a latent diffusion model. Our framework processes film clips as input and generates music that aligns with a general theme while offering…

Multimedia · Computer Science 2024-11-13 F. Qi , L. Ni , C. Xu

Generating realistic 3D indoor scenes from user inputs remains a challenging problem in computer vision and graphics, requiring careful balance of geometric consistency, spatial relationships, and visual realism. While neural generation…

Computer Vision and Pattern Recognition · Computer Science 2025-06-30 Mengqi Zhou , Xipeng Wang , Yuxi Wang , Zhaoxiang Zhang

We introduce SceneLinker, a novel framework that generates compositional 3D scenes via semantic scene graph from RGB sequences. To adaptively experience Mixed Reality (MR) content based on each user's space, it is essential to generate a 3D…

Computer Vision and Pattern Recognition · Computer Science 2026-02-04 Seok-Young Kim , Dooyoung Kim , Woojin Cho , Hail Song , Suji Kang , Woontack Woo

This paper presents Task 7 at the DCASE 2024 Challenge: sound scene synthesis. Recent advances in sound synthesis and generative models have enabled the creation of realistic and diverse audio content. We introduce a standardized evaluation…

Artificial Intelligence · Computer Science 2025-01-16 Mathieu Lagrange , Junwon Lee , Modan Tailleur , Laurie M. Heller , Keunwoo Choi , Brian McFee , Keisuke Imoto , Yuki Okamoto

Segmenting long-form videos into semantically coherent scenes is a fundamental task in large-scale video understanding. Existing encoder-based methods are limited by visual-centric biases, classify each shot in isolation without leveraging…

Computer Vision and Pattern Recognition · Computer Science 2026-03-24 Nimrod Berman , Adam Botach , Emanuel Ben-Baruch , Shunit Haviv Hakimi , Asaf Gendler , Ilan Naiman , Erez Yosef , Igor Kviatkovsky

We propose a data-driven approach for context-aware person image generation. Specifically, we attempt to generate a person image such that the synthesized instance can blend into a complex scene. In our method, the position, scale, and…

Computer Vision and Pattern Recognition · Computer Science 2025-02-19 Prasun Roy , Saumik Bhattacharya , Subhankar Ghosh , Umapada Pal , Michael Blumenstein

Scene parsing is a technique that consist on giving a label to all pixels in an image according to the class they belong to. To ensure a good visual coherence and a high class accuracy, it is essential for a scene parser to capture image…

Computer Vision and Pattern Recognition · Computer Science 2013-06-13 Pedro H. O. Pinheiro , Ronan Collobert

The convergence of 3D geometric perception and video synthesis has created an unprecedented demand for large-scale video data that is rich in both semantic and spatio-temporal information. While existing datasets have advanced either 3D…

Computer Vision and Pattern Recognition · Computer Science 2026-04-28 Yunnan Wang , Kecheng Zheng , Jianyuan Wang , Minghao Chen , David Novotny , Christian Rupprecht , Yinghao Xu , Xing Zhu , Wenjun Zeng , Xin Jin , Yujun Shen

The recent innovations and breakthroughs in diffusion models have significantly expanded the possibilities of generating high-quality videos for the given prompts. Most existing works tackle the single-scene scenario with only one video…

Computer Vision and Pattern Recognition · Computer Science 2024-09-17 Fuchen Long , Zhaofan Qiu , Ting Yao , Tao Mei

Automatic movie narration aims to generate video-aligned plot descriptions to assist visually impaired audiences. Unlike standard video captioning, it involves not only describing key visual details but also inferring plots that unfold…

Computer Vision and Pattern Recognition · Computer Science 2024-10-21 Zihao Yue , Yepeng Zhang , Ziheng Wang , Qin Jin

Training robots in simulation requires diverse 3D scenes that reflect the specific challenges of downstream tasks. However, scenes that satisfy strict task requirements, such as high-clutter environments with plausible spatial arrangement,…

Robotics · Computer Science 2025-08-27 Nicholas Pfaff , Hongkai Dai , Sergey Zakharov , Shun Iwase , Russ Tedrake

Video generation has witnessed great success recently, but their application in generating long videos still remains challenging due to the difficulty in maintaining the temporal consistency of generated videos and the high memory cost…

Computer Vision and Pattern Recognition · Computer Science 2024-07-19 Wei Feng , Xin Wang , Hong Chen , Zeyang Zhang , Wenwu Zhu

We present a video generation model that accurately reproduces object motion, changes in camera viewpoint, and new content that arises over time. Existing video generation methods often fail to produce new content as a function of time…

Computer Vision and Pattern Recognition · Computer Science 2022-06-10 Tim Brooks , Janne Hellsten , Miika Aittala , Ting-Chun Wang , Timo Aila , Jaakko Lehtinen , Ming-Yu Liu , Alexei A. Efros , Tero Karras

We are living in a flourishing era of digital media, where everyone has the potential to become a personal filmmaker. Current research on video generation suggests a promising avenue for controllable film creation in pixel space using…

Computer Vision and Pattern Recognition · Computer Science 2025-07-03 Weiliang Chen , Fangfu Liu , Diankun Wu , Haowen Sun , Jiwen Lu , Yueqi Duan

Many compelling video processing effects can be achieved if per-pixel depth information and 3D camera calibrations are known. However, the success of such methods is highly dependent on the accuracy of this "scene-space" information. We…

Computer Vision and Pattern Recognition · Computer Science 2021-02-08 Felix Klose , Oliver Wang , Jean-Charles Bazin , Marcus Magnor , Alexander Sorkine-Hornung
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